Metrics question
There is a spike in Lyft ride cancellations this week. Why could this be the case?
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What this question tests
Tests root-cause diagnosis of a metric spike using a structured hypothesis-and-segmentation approach.
How to approach it
- Split cancellations by who initiated them, rider versus driver, since the causes and fixes differ completely.
- Hypothesize rider-side causes: longer-than-usual ETAs from a driver shortage, surge pricing prompting a cancel-and-rebook, or an app matching bug.
- Hypothesize driver-side causes: low fares relative to trip length, a problematic app update, or driver incentive changes reducing supply in certain zones.
- Segment the data by time of day, city or zone, and platform to see if this is localized or a global issue.
- Cross-reference with any recent app releases or known supply shortages in the spike window before proposing a fix.
What a strong answer includes
- Separates rider- versus driver-initiated cancellations as the first diagnostic split, the most useful bucketing for this exact metric.
- Ties the investigation to concrete next steps, checking recent releases and ops changes, not abstract look-into-it language.
- Segments by time, zone and platform before proposing any fix.
Common mistakes
- Treating cancellations as one undifferentiated bucket without splitting rider versus driver-initiated.
- Jumping to a fix before segmenting by time, zone or platform to find the actual pattern.
Likely follow-up questions
- How would you distinguish a bug-caused spike from a market-conditions-caused spike?
- What immediate mitigation would you take while root cause is still being investigated?
More metrics questions
- Late deliveries lead to customer churn. What data we should look at to prove this hypothesis for a food delivery app?PayPal · Metrics · Medium
- How would reduce cancellations for Uber?Shopify · Metrics · Medium
- There is a data point that indicates that there are more Uber drop-offs at the airport than pick-ups from the airport. Why is this the case and what would you do within the product to change that?PayPal · Metrics · Hard
- How would you measure the success of Uber Ride?Lyft · Metrics · Easy
- If a large number of drivers are dropping out of a particular city, why would it be?Lyft · Metrics · Medium
- Drivers are dropping out of a city on Lyft. How do you figure out what's going on?PayPal · Metrics · Medium
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Learn the skill behind it
Chapters of the AI PM course that teach what this question tests.
- Chapter 9: Prove it paid off: outcomes, economics, and pricing
- Chapter 2: Data fluency: SQL, logs, and reading the truth yourself
- Chapter 14: Get the job: the AI PM interview loop